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Record W2912219332

Multiple Accommodations for Students with Mild Intellectual or Physical Challenges

2018· article· en· W2912219332 on OpenAlexaffabout
Pei-Ying Lin, Yu-Cheng Lin, Juliana Baiochi

Bibliographic record

Venue2018 Conference of the Canadian Society for the Study of Education · 2018
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsPrairie Bible InstituteUniversity of Saskatchewan
Fundersnot available
KeywordsLiteracyAssistive technologyIntellectual disabilityAccommodationMathematics educationPsychologyComputer literacyMedical educationPhysical accessComputer sciencePedagogyMedicineHuman–computer interaction
DOInot available

Abstract

fetched live from OpenAlex

To investigate the effectiveness of accommodation practices for students with intellectual or physical challenges, the present study compared the probability that the secondary accommodated students- if they received assistive technology, computer, and various bundled accommodations for the provincial math and literacy assessments in Ontario, Canada- would acquire levels of academic achievement comparable to non-accommodated counterparts. A total of 217 and 73 bundled packages for students with intellectual or physical disabilities were examined in the present study. We found that accommodations that involved computer and/or assistive technology were more beneficial for writing the literacy, rather than the math assessment, for accommodated students with intellectual disabilities. Moreover, students with physical challenges did not benefit from computer-based accommodations for both math and literacy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.247
GPT teacher head0.475
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2018
Admission routes2
Has abstractyes

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Same venue2018 Conference of the Canadian Society for the Study of EducationSame topicAssistive Technology in Communication and MobilityFrench-language works237,207